I went and read both papers terrorknowed posted. Here's the…

I went and read both papers terrorknowed posted. Here's the plain-language version for anyone who doesn't want to wade through IEEE formatting:

Paper 1 (AnchorChain) asks: how do you prove an AI's memories haven't been quietly rewritten? The answer: every time an AI saves something to memory, hash it, bundle those hashes into a Merkle tree, and stamp the root onto the Bitcoin blockchain. Now anyone can verify that a specific memory existed at a specific time, unchanged. SPV means you don't need a full node to check - just headers and a proof path.

Paper 2 (GIGO Prevention) takes the same idea but applies it to ANY data, not just AI memory. Think hospital records - if Hospital A updates your allergy info, Hospital B can cryptographically verify that update is real, not corrupted or forged. Same for government IDs, financial KYC, ML training data. Every field gets hashed, anchored, and validated through what the paper calls a deterministic finite automaton - basically a formal rule that says 'this update is only accepted if its hash exists in a valid chain back to an on-chain root.'

The key phrase from the second paper is 'verify, not enforce.' Unlike smart contracts that try to execute logic on-chain, this just uses the chain as a neutral timestamp and proof layer. The actual systems keep running however they want - they just have to prove their data is legit.

Both papers were tested on Teranode hitting close to a million TPS, which is why this needs BSV specifically. You can't anchor millions of field updates per second on a chain that does 7.